Road to Recovery

Scatter Quadrant

Photo by Matt Collamer on Unsplash

Everything will be okay in the end. If it’s not okay, it’s not the end…
— John Lennon

Ingest the source

df = read.csv("archetypes/road-to-recovery/road-to-recovery.csv", header = TRUE, stringsAsFactors = FALSE)
df

Wrangle

select, clean, and cast data types

df <- df[-12,]

colnames(df)[1] <- "country" # Changing Column Name


df$Mobility.Rate<-as.numeric(gsub("\\%","",df$Mobility.Rate)) # Removin percent sign
df$Recovery.Rate<-as.numeric(gsub("\\%","",df$Recovery.Rate))
df$Total.Cases<-as.numeric(gsub("\\,","",df$Total.Cases))
df$Total.Recovered<-as.numeric(gsub("\\,","",df$Total.Recovered))

library(countrycode)
df$iso <- tolower(countrycode(sourcevar = df[, "country"],
                            origin = "country.name",
                            destination = "iso2c"))

df

Scatter Quadrant Plot

theme_opts <- theme(
    text = element_text(family = "inconsolata"), 
    plot.title = element_text(color = "black", size = 20, face = "bold"),
    plot.subtitle = element_text(color = "black", size = 15),
    plot.caption = element_text(color = "#555555", size = 8),
    axis.text = element_text(size=10),
    panel.border = element_blank(),
    panel.background = element_blank(),
    legend.title = element_text(color = "black", size = 8, face = "bold"), 
    legend.text = element_text(color = "black", size = 8),
    legend.position = "none"
)


v1 <- ggplot(df, aes(x=Recovery.Rate, y=Mobility.Rate, country = iso, label=country)) +
  annotate("rect", xmin = 0, xmax = 50, ymin = -50, ymax = 20, fill= "white", color = "white")  + 
  annotate("rect", xmin = 50, xmax = 100, ymin = -50, ymax = 20, fill= "#c3e8ee", color = "white") + 
  annotate("rect", xmin = 0, xmax = 50, ymin = -120, ymax = -50, fill= "#f3d4d9", color = "white") + 
  annotate("rect", xmin = 50, xmax = 100, ymin = -120, ymax = -50, fill= "white", color = "white")+
  annotate("text", x = 60, y=15, label= "High Mobility, High recovery\nLifted Restrictions &\nPeople going back to work")+
  annotate("text", x = 10, y=-60, label= "Low Mobility, Low recovery\nRemaining Indoors") +
  annotate("text", x = 10, y=15, label= "High Mobility, Low recovery\nAllowing activity\nPossible surge in Future") +
  annotate("text", x = 60, y=-115, label= "Low Mobility, High recovery\nPlaying it Safe") +
  geom_point() +
  geom_flag()+
  geom_text_repel() +
  scale_y_continuous(breaks=c(20, 0, -40, -80, -120),
                  labels=c('20%', '0', '-40%', '-80%', '-12%')) +
  scale_x_continuous(breaks=c(0, 25, 50, 75, 100),
                  labels=c('0', '25%', '50%', '75%', '100%'))+
      labs(y="Mobility Rate",
           x = "Recovery Rate",
       title = "The Road to Recovery",
       subtitle = "Which Economies are Reopening? \nThe higher the mobility rate, the more activity this signifies")+
  theme_opts


girafe(ggobj = v1, width_svg = 16, height_svg = 15,
       options = list(opts_sizing(rescale = TRUE, width = 0.8)))

References

Citations and data sources

Inspiration and data: The Visual Capitalist, GO